7 citations · 15 across the 6 of their papers we have counts for
9 papers · 1 filter
Drawing Conclusions from Draws: Rethinking Preference Semantics in Arena-Style LLM Evaluation
Raphael Tang, Crystina Zhang, Wenyan Li +3
In arena-style evaluation of large language models (LLMs), two LLMs respond to a user query, and the user chooses the winning response or deems the "battle" a draw, resulting in an…
Lost in Inference: Rediscovering the Role of Natural Language Inference for Large Language Models
Lovish Madaan, David Esiobu, Pontus Stenetorp +2
In the recent past, a popular way of evaluating natural language understanding (NLU), was to consider a model's ability to perform natural language inference (NLI) tasks. In this p…
Multilingual Pretraining Using a Large Corpus Machine-Translated from a Single Source Language
Jiayi Wang, Yao Lu, Maurice Weber +4
English, as a very high-resource language, enables the pretraining of high-quality large language models (LLMs). The same cannot be said for most other languages, as leading LLMs s…
Quantifying Generative Media Bias with a Corpus of Real-world and Generated News Articles
Filip Trhlik, Pontus Stenetorp
Large language models (LLMs) are increasingly being utilised across a range of tasks and domains, with a burgeoning interest in their application within the field of journalism. Th…
Non-parametric, Nearest-neighbor-assisted Fine-tuning for Neural Machine Translation
Jiayi Wang, Ke Wang, Yuqi Zhang +2
Non-parametric, k-nearest-neighbor algorithms have recently made inroads to assist generative models such as language models and machine translation decoders. We explore whether su…
Graph Attention with Hierarchies for Multi-hop Question Answering
Yunjie He, Philip John Gorinski, Ieva Staliunaite +1
Multi-hop QA (Question Answering) is the task of finding the answer to a question across multiple documents. In recent years, a number of Deep Learning-based approaches have been p…